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In this article Agentic cloud operations: Introducing Azure Copilot Azure’s AI infrastructure: The backbone of modernization Building for trust: Resiliency, operational excellence, and security What does modernizing workloads look like today? Looking ahead The cloud is more than just a platform—it’s the engine of transformation for every organization. This year at Microsoft Ignite 2025, we’re…
Innovation in AI is about empowering every developer and organization with the freedom to choose the right intelligence for every challenge. In today’s landscape, where business needs span from real-time chatbots to deep research agents, model choice is an essential engine of progress. Microsoft Foundry already offers the widest selection of models of any cloud…
Today, we are unveiling the next Fairwater site of Azure AI datacenters in Atlanta, Georgia. This purpose-built datacenter is connected to our first Fairwater site in Wisconsin, prior generations of AI supercomputers and the broader Azure global datacenter footprint to create the world’s first planet-scale AI superfactory. By packing computing power more densely than ever…
Across industries, organizations are moving from experimentation with AI to operationalizing it within business-critical workflows. At Microsoft, we are partnering with UiPath—a preferred enterprise agentic automation platform on Azure—to empower customers with integrated solutions that combine automation and AI at scale. One example is Azure AI Foundry agents and UiPath agents (built on Azure AI…
Microsoft and NVIDIA are deepening our partnership to power the next wave of AI industrial innovation. For years, our companies have helped fuel the AI revolution, bringing the world’s most advanced supercomputing to the cloud, enabling breakthrough frontier models, and making AI more accessible to organizations everywhere. Today, we’re building on that foundation with new…
In the early days of the AI shift, AI applications were largely built as thin layers on top of off-the-shelf foundation models. But as developers began tackling more complex use cases, they quickly encountered the limitations of simply using RAG on top of off-the-shelf models. While this approach offered a fast path to production, it…